The Analysis of Assumptions in Model Bases Using Metagraphs

Amit Basu and Robert W. Blanning
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Amit Basu: Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203
Robert W. Blanning: Owen Graduate School of Management, Vanderbilt University, Nashville, Tennessee 37203

Management Science, 1998, vol. 44, issue 7, 982-995

Abstract: Decision models are often based on certain assumptions as to their validity. Relevant assumptions may include value-based assumptions, such as limitations on the range or values of some input variables or exogenous factors, as well as assumptions about model structure (e.g., linearity). In a model base consisting of many models, there may be several models (or collections of models) that can be used to solve a particular problem. We may wish to know what the applicable models are, what assumptions are associated with these models, and whether a given set of assumptions is necessary and/or sufficient for solving the problem. We describe an analytical approach, based on a graph-theoretic construct called a metagraph, and show how it can be used to represent and analyze assumptions in model bases.

Keywords: Assumptions; Model Management; Graph Theory; Decision Support Systems; Information Systems (search for similar items in EconPapers)
Date: 1998
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:44:y:1998:i:7:p:982-995

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